A method and system for automatically verifying various disaster data in coal mines

Abstract

The present invention provides a method and system for automatically verifying various coal mine disaster data, including: obtaining the expected coal mine disaster data to be verified, determining formatting parameters for the coal mine disaster data based on multi-dimensional attributes of the expected coal mine disaster data, and constructing a data model; performing custom rule configuration and scenario configuration on the data model based on verification attribute items, and associating disaster indicators with the results of the custom rule configuration and scenario configuration to obtain an automatic verification model for coal mine disaster data; performing model parsing on the accessed disaster data stream based on the automatic verification model for coal mine disaster data to determine corresponding verification rules, and performing data verification on the disaster data stream based on the verification rules; recording and analyzing the data verification results, generating a verification report of the verification results and analysis results, and viewing and managing the verification report. It ensures the efficiency and accuracy of automatically verifying coal mine disaster data.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and particularly relates to a method and system for automatically verifying various coal mine disaster data. Background Art

[0002] At present, during the coal mine production process, various disasters are faced, such as gas explosion, coal dust explosion, roof accident, water inrush accident, etc. In order to effectively prevent these disasters, a large amount of data related to disasters needs to be monitored and analyzed;

[0003] However, for the original data verification work, not only a large amount of manual participation is required, but there is a lot of repetitive work in the data verification content of various disasters. Its standards and rules are diverse, and the relationship between data and rules is chaotic, which is not convenient for unified management, analysis, and expansion, thus greatly reducing the verification effect of various disaster data;

[0004] Therefore, in order to overcome the above defects, the present invention provides a method and system for automatically verifying various coal mine disaster data. Summary of the Invention

[0005] The present invention provides a method and system for automatically verifying various coal mine disaster data, which is used to effectively construct a data model by determining the multi-dimensional attributes of the expected coal mine disaster data to be verified and determining the formatting parameters for the coal mine disaster data according to the multi-dimensional attributes. Secondly, custom rules configuration and scenario configuration are performed on the data model according to the verification attribute items, and the disaster indicators are associated with the configuration results to effectively construct an automatic verification model for coal mine disaster data, providing convenience and guarantee for the automatic verification of coal mine disaster data. Finally, the automatic verification model for coal mine disaster data is used to parse and verify the accessed disaster data stream, generate corresponding verification reports according to the verification results, and view and manage the verification reports, ensuring the efficiency and accuracy of the automatic verification of coal mine disaster data. At the same time, automated processing reduces manual participation, and custom standardized rules and scenarios can flexibly and efficiently verify data for different disasters.

[0006] The present invention provides a method for automatically verifying various coal mine disaster data, including:

[0007] Step 1: Obtain the expected coal mine disaster data to be verified, and determine the formatting parameters for the coal mine disaster data based on the multi-dimensional attributes of the expected coal mine disaster data to construct a data model;

[0008] Step 2: Perform custom rules configuration and scenario configuration on the data model based on the verification attribute items, and associate the disaster indicators with the custom rules configuration and scenario configuration results to obtain an automatic verification model for coal mine disaster data;

[0009] Step 3: Based on the coal mine disaster data automatic verification model, parse the accessed disaster data stream to determine the corresponding verification rules, and perform data verification on the disaster data stream based on the verification rules;

[0010] Step 4: Record and analyze the data verification results, generate a verification report of the verification results and analysis results, and view and manage the verification report.

[0011] Preferably, for a method of automatically verifying various coal mine disaster data, in step 1, obtaining the expected coal mine disaster data to be verified includes:

[0012] Obtain the system composition of the coal mine, and determine the original disaster data generated during the operation of the coal mine based on the system composition;

[0013] Based on the original disaster data, obtain the expected coal mine disaster data to be verified, and extract the data status representation of the expected coal mine disaster data to be verified;

[0014] Based on the data status representation, divide the preset coal mine disaster data to be verified into disaster data types, and access the coal mine disaster knowledge base based on the disaster data type division result to determine the management dimension for each disaster data type;

[0015] Based on the management dimension, obtain the multi-dimensional attributes of the expected coal mine disaster data to be verified under each disaster data type.

[0016] Preferably, for a method of automatically verifying various coal mine disaster data, step 1: Obtain the expected coal mine disaster data to be verified, and determine the formatting parameters for the coal mine disaster data based on the multi-dimensional attributes of the expected coal mine disaster data to be verified, and construct a data model, including:

[0017] Obtain the multi-dimensional attributes of the expected coal mine disaster data to be verified, and determine the semantic features of each dimension attribute;

[0018] At the same time, based on the management terminal, obtain the verification process and verification business for each dimension attribute in the expected coal mine disaster data of different categories, and determine the differential formatting requirements for each dimension attribute in the expected coal mine disaster data of different categories based on the semantic features, verification process and verification business;

[0019] Based on the differential formatting requirements, determine the formatting parameters for the coal mine disaster data, and classify and record the formatting parameters of different dimension attributes of different categories of coal mine disaster data to obtain a data model.

[0020] Preferably, for a method of automatically verifying various coal mine disaster data, in step 2, perform custom rule configuration and scenario configuration on the data model based on the verification attribute items, including:

[0021] Based on the management terminal, obtain the verification objectives for various coal mine disaster data, and group and divide the multi-dimensional attributes of the expected coal mine disaster data to be verified based on the verification objectives to obtain the verification attribute items corresponding to each verification objective;

[0022] Respectively determine the sample representations of different verification attribute items under each verification objective, and determine the data types of different verification attribute items based on the sample representations;

[0023] Based on the coal mine disaster management system, retrieve the basic business logics of different verification attribute items, and determine the underlying logic verification focuses of different verification attribute items based on the basic business logics. At the same time, determine the custom verification focuses for different verification attribute items based on the management objectives;

[0024] Determine the verification rules for different verification attribute items based on the data types, and determine the rule contents corresponding to the verification rules based on the underlying logic verification focuses and custom verification focuses;

[0025] Nest the rule contents with the verification rules to obtain the target verification rules, and obtain the available format requirements for the target verification rules based on the nesting results;

[0026] Perform content writing conversion on the target verification rules based on the available format requirements, obtain the custom rule configuration results based on the content writing conversion results, and perform conversion on the data model based on the custom rule configuration results to obtain the corresponding rule model;

[0027] Based on the management terminal, obtain the pre-application scenarios for the rule model, and extract the scenario limiting factors of the pre-application scenarios;

[0028] Determine the application conditions and requirements for different pre-application scenarios based on the scenario limiting factors, and group and classify the rule models based on the application conditions and requirements to obtain the rule model sets corresponding to each pre-application scenario;

[0029] At the same time, determine the adaptive correction parameters for the rule parameters of each rule model in the corresponding rule model sets based on the application conditions and requirements of different pre-application scenarios, and perform adaptive adjustment on the rule parameters of each rule model based on the adaptive correction parameters to complete the scenario configuration of the rule model.

[0030] Preferably, for a method for automatically verifying various coal mine disaster data, in step 2, associate the disaster indicators with the custom rule configuration and scenario configuration results to obtain an automatic verification model for coal mine disaster data, including:

[0031] Obtain the disaster indicators, and receive the scenario association instructions for the disaster indicators submitted by the management user based on the configuration page;

[0032] Determine the association relationship between the disaster indicators and the scenario configuration results based on the scenario - related instructions, and generate a drainage reference table for disaster data based on the association relationship;

[0033] Perform routing adaptation of the data flow interface for the custom rule configuration and the scenario configuration results based on the drainage reference table, and obtain an automatic verification model for coal mine disaster data based on the routing adaptation result.

[0034] Preferably, for a method of automatically verifying multiple types of coal mine disaster data, in step 3, based on the automatic verification model for coal mine disaster data, perform model parsing on the accessed disaster data flow, determine the corresponding verification rules, and perform data verification on the disaster data flow based on the verification rules, including:

[0035] Obtain the disaster data flow, input the disaster data flow into the automatic verification model for coal mine disaster data for model parsing, and obtain the specific verification rules corresponding to the disaster data flow;

[0036] Divide the disaster data flow into data groups to be verified respectively based on the attribute - limiting requirements of the specific verification rules. At the same time, extract the verification dimensions of the specific verification rules, and map - match the specific verification rules with the data groups to be verified based on the verification dimensions;

[0037] Based on the mapping - matching result, call the entire verification process corresponding to the specific verification rule to perform automatic data verification on the data groups to be verified under the corresponding verification dimensions.

[0038] Preferably, for a method of automatically verifying multiple types of coal mine disaster data, in step 4, record and analyze the data verification results to generate a verification report of the verification results and the analysis results, including:

[0039] Obtain the data verification results for the coal mine disaster data and record the data verification results;

[0040] Based on the recorded results, split the data verification results into a set of verified data and a set of unverified data, and trace the source data of the set of unverified data to obtain the corresponding original coal mine disaster data and the reasons for non - verification;

[0041] Configure the original coal mine disaster data and the reasons for non - verification corresponding to the set of unverified data as a drill - down data viewing list;

[0042] At the same time, generate a comparison chart of the set of verified data and the set of unverified data based on the verification time, and associate and bind the drill - down data viewing list with the set of unverified data in the comparison chart;

[0043] Generate a verification report of the verification results and the analysis results based on the association - binding result.

[0044] Preferably, for a method for automatically verifying multiple disaster data in coal mines, in step 4, the verification report is viewed and managed, including:

[0045] Obtaining the obtained verification report and determining the viewing method of the verification report, where the viewing method includes previewing, downloading, and printing;

[0046] Configuring background management parameters for the verification report based on the viewing method, and opening multi-channel viewing permissions for the verification report based on the background management parameter configuration;

[0047] Effectuating the permissions for the verification report based on the multi-channel viewing permissions to complete the viewing management of the verification report.

[0048] The present invention provides a system for automatically verifying multiple disaster data in coal mines, including:

[0049] A data model construction module, configured to obtain expected coal mine disaster data to be verified, and determine formatting parameters for the coal mine disaster data based on multi-dimensional attributes of the expected coal mine disaster data, and construct a data model;

[0050] A verification model construction module, configured to perform custom rule configuration and scenario configuration on the data model based on verification attribute items, and associate disaster indicators with the results of the custom rule configuration and scenario configuration to obtain an automatic verification model for coal mine disaster data;

[0051] A data verification module, configured to perform model parsing on the accessed disaster data stream based on the automatic verification model for coal mine disaster data to determine corresponding verification rules, and perform data verification on the disaster data stream based on the verification rules;

[0052] A verification report management module, configured to record and analyze the data verification results, generate a verification report of the verification results and analysis results, and perform viewing management on the verification report.

[0053] Preferably, for a system for automatically verifying multiple disaster data in coal mines, the data model construction module includes:

[0054] A data acquisition unit, configured to obtain the system composition of the coal mine and determine the original disaster data generated during the operation of the coal mine based on the system composition;

[0055] An attribute determination unit, configured to:

[0056] Obtain expected coal mine disaster data to be verified based on the original disaster data, and extract the data state representation of the expected coal mine disaster data;

[0057] Perform disaster data type division on the preset coal mine disaster data to be verified based on the data state representation, and access the coal mine disaster knowledge base based on the disaster data type division result to determine the management dimension for each disaster data type;

[0058] Based on the management dimension, multi-dimensional attributes of the expected verified coal mine disaster data are obtained for each disaster data type.

[0059] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0060] By determining the multi-dimensional attributes of the expected verified coal mine disaster data and determining the formatting parameters for the coal mine disaster data according to the multi-dimensional attributes, an effective construction of the data model is achieved. Secondly, according to the verification attribute items, custom rule configuration and scenario configuration are performed on the data model, and the disaster indicators are associated with the configuration results, realizing an effective construction of the automatic verification model for coal mine disaster data, providing convenience and guarantee for the automatic verification of coal mine disaster data. Finally, through the automatic verification model of coal mine disaster data, the parsed disaster data stream and data verification are performed on the accessed data, and the corresponding verification report is generated according to the verification results, and the verification report is viewed and managed, ensuring the efficiency and accuracy of the automatic verification of coal mine disaster data. At the same time, the automated processing reduces manual participation, and the custom standardized rules and scenarios can flexibly and efficiently perform verification work for different disaster data.

[0061] Other features and advantages of the present invention will be described in the following specification, and in part will become apparent from the specification or be understood by implementing the present invention. The objectives and other advantages of the present invention can be achieved and obtained through the structure specifically pointed out in this application document.

[0062] The technical solutions of the present invention will be further described in detail below through the accompanying drawings and embodiments. Description of the Drawings

[0063] The accompanying drawings are used to provide a further understanding of the present invention, and constitute a part of the specification, and are used to explain the present invention together with the embodiments of the present invention, and do not constitute a limitation to the present invention. In the accompanying drawings:

[0064] Figure 1 is a flowchart of a method for automatically verifying various coal mine disaster data in an embodiment of the present invention;

[0065] Figure 2 is a schematic diagram of the data model construction of gas data in a method for automatically verifying various coal mine disaster data in an embodiment of the present invention;

[0066] Figure 3 is an example diagram of custom rule configuration in a method for automatically verifying various coal mine disaster data in an embodiment of the present invention;

[0067] Figure 4 is an example diagram of data verification in a method for automatically verifying various coal mine disaster data in an embodiment of the present invention;

[0068] Figure 5 This is a comparison graph of the passed verification set and the unpassed verification set in a method for automatically verifying various disaster data in a coal mine according to an embodiment of the present invention;

[0069] Figure 6 This is a structural diagram of a system for automatically verifying various disaster data in a coal mine according to an embodiment of the present invention. Specific Embodiments

[0070] The following describes the preferred embodiments of the present invention with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only for illustrating and explaining the present invention, and are not used to limit the present invention.

[0071] Embodiment 1:

[0072] This embodiment provides a method for automatically verifying various disaster data in a coal mine, as Figure 1 shown, including:

[0073] Step 1: Obtain the expected coal mine disaster data to be verified, and determine the formatting parameters for the coal mine disaster data based on the multi-dimensional attributes of the expected coal mine disaster data, and construct a data model;

[0074] Step 2: Perform custom rule configuration and scenario configuration on the data model based on the verification attribute items, and associate the disaster indicators with the results of the custom rule configuration and scenario configuration to obtain an automatic verification model for coal mine disaster data;

[0075] Step 3: Based on the automatic verification model for coal mine disaster data, perform model parsing on the accessed disaster data stream, determine the corresponding verification rules, and perform data verification on the disaster data stream based on the verification rules;

[0076] Step 4: Record and analyze the data verification results, generate a verification report of the verification results and analysis results, and view and manage the verification report.

[0077] In this embodiment, the expected coal mine disaster data to be verified refers to the coal mine disaster data that needs to be verified and managed.

[0078] In this embodiment, the multi-dimensional attributes refer to different attributes included in the expected coal mine disaster data to be verified, such as attributes such as time, gas concentration, and disaster data type.

[0079] In this embodiment, the formatting parameters refer to the methods or measures for formatting the coal mine disaster data with different multi-dimensional attributes.

[0080] In this embodiment, the data model refers to the result obtained after formatting and defining the coal mine disaster data with multi-dimensional attributes, and is used to represent the specific formatting steps or standards for the coal mine disaster data.

[0081] In this embodiment, the verification attribute item refers to the data item for which data verification needs to be performed.

[0082] In this embodiment, the custom rule configuration and scenario configuration refer to the configuration of the verification rules and application scenarios for the data model, so as to facilitate the corresponding verification operations on various disaster data through the configured rules and scenarios.

[0083] In this embodiment, the disaster index is used to represent the types of disaster data applicable to different verification rules and scenarios, that is, the types of disaster data that can be processed.

[0084] In this embodiment, the coal mine disaster data automatic verification model refers to the finally obtained tool that can perform coal mine disaster data verification.

[0085] The working principle and beneficial effects of the above technical solution are as follows: By determining the multi-dimensional attributes of the coal mine disaster data to be verified, and determining the formatting parameters for the coal mine disaster data according to the multi-dimensional attributes, an effective construction of the data model is realized. Secondly, according to the verification attribute items, the custom rule configuration and scenario configuration of the data model are carried out, and the disaster index is associated with the configuration result, so as to effectively construct the coal mine disaster data automatic verification model, providing convenience and guarantee for the automatic verification of coal mine disaster data. Finally, through the coal mine disaster data automatic verification model, the parsed and verified disaster data stream is accessed, and the corresponding verification report is generated according to the verification result, and the verification report is viewed and managed, ensuring the efficiency and accuracy of the automatic verification of coal mine disaster data. At the same time, the automated processing reduces manual participation, and the custom standardized rules and scenarios can flexibly and efficiently perform verification work for different disaster data.

[0086] Embodiment 2:

[0087] Based on Embodiment 1, this embodiment provides a method for automatically verifying various coal mine disaster data. In step 1, obtaining the coal mine disaster data to be verified includes:

[0088] Obtaining the system composition of the coal mine, and determining the original disaster data generated during the operation of the coal mine based on the system composition;

[0089] Obtaining the coal mine disaster data to be verified based on the original disaster data, and extracting the data status representation of the coal mine disaster data to be verified;

[0090] Classify the preset verified coal mine disaster data based on the data status representation, and access the coal mine disaster knowledge base based on the classification result of the disaster data type to determine the management dimension for each disaster data type;

[0091] Obtain the multi-dimensional attributes of the expected verified coal mine disaster data for each disaster data type based on the management dimension.

[0092] In this embodiment, the system composition refers to the components of the coal mine, which facilitates determining the data types generated during the operation of the coal mine system.

[0093] In this embodiment, the original disaster data refers to the specific disaster data generated during the production or operation of the coal mine determined according to the system composition.

[0094] In this embodiment, the data status representation refers to the characteristics or phenomena presented by the expected verified coal mine disaster data, including data value characteristics and structural conditions, etc.

[0095] In this embodiment, the coal mine disaster knowledge base is pre-constructed and used to store the management dimensions for each disaster data type. Among them, the management dimension refers to the management aspects of each disaster data type, including data compliance and legality, etc.

[0096] The working principle and beneficial effects of the above technical solution are as follows: By determining the system composition of the coal mine, the original disaster data generated during the operation of the coal mine is determined through the system composition, and then the expected verified coal mine disaster data is locked. Secondly, the data status representation of the expected verified coal mine disaster data is determined, and the classification of the disaster data type and the management dimension for each disaster data type are determined according to the data status representation. Finally, the multi-dimensional attributes of the expected verified coal mine disaster data for each disaster data type are obtained according to the management dimension, which provides convenience for the automatic verification of coal mine disaster data.

[0097] Embodiment 3:

[0098] Based on Embodiment 1, this embodiment provides a method for automatically verifying various coal mine disaster data, as Figure 2 shown, Step 1: Obtain the expected verified coal mine disaster data, and determine the formatting parameters for the coal mine disaster data based on the multi-dimensional attributes of the expected verified coal mine disaster data, and construct a data model, including:

[0099] Obtain the multi-dimensional attributes of the expected verified coal mine disaster data, and determine the semantic features of each dimension attribute;

[0100] Meanwhile, based on the management terminal, obtain the verification processes and verification services for each dimensional attribute in the expected verification of coal mine disaster data of different categories, and determine the differential formatting requirements for each dimensional attribute in the expected verification of coal mine disaster data of different categories based on semantic features, verification processes, and verification services;

[0101] Determine the formatting parameters for the coal mine disaster data based on the differential formatting requirements, and classify and record the formatting parameters for different dimensional attributes of different categories of coal mine disaster data to obtain a data model.

[0102] In this embodiment, for example, an abstract model is established for gas disaster data: 140XXXXXX771; XX Coal Mine; 2024-08-20 14:14:13~14060201277101MN0043586; Laser Methane; XX Methane T2; 0.00; 2024-08-20 14:13:49~After formatting: 1.mineCode;mineName;dataTime;

[0103] 2.sensorCode;sensorType;sensorName;sensorValue;sensorTime The schematic diagram of the data model construction of gas data is as Figure 2 shown.

[0104] In this embodiment, the semantic feature refers to the core content corresponding to each dimensional attribute or the information content corresponding to each dimensional attribute.

[0105] In this embodiment, the differential formatting requirement refers to different formatting requirements corresponding to different dimensional attributes, that is, the format requirements corresponding to different dimensional attributes are different.

[0106] The working principle and beneficial effects of the above technical solution are: By analyzing the multi-dimensional attributes of the expected verification of coal mine disaster data, the semantic features, verification processes, and verification services corresponding to each dimensional attribute are locked, and then the differential formatting requirements for each dimensional attribute in the expected verification of coal mine disaster data are determined according to the semantic features, verification processes, and verification services. Finally, the formatting parameters of the coal mine disaster data are locked according to the differential formatting requirements, and finally, an accurate and effective data model is constructed, providing convenience and guarantee for the automatic verification of various coal mine disaster data.

[0107] Embodiment 4:

[0108] Based on Embodiment 1, this embodiment provides a method for automatic verification of various coal mine disaster data, as Figure 3 shown. In step 2, perform custom rule configuration and scenario configuration on the data model based on the verification attribute items, including:

[0109] Based on the management terminal, obtain the verification objectives for various coal mine disaster data, and group-divide the multi-dimensional attributes of the expected coal mine disaster data to be verified based on the verification objectives to obtain the verification attribute items corresponding to each verification objective;

[0110] Determine the sample representations of different verification attribute items under each verification objective respectively, and determine the data types of different verification attribute items based on the sample representations;

[0111] Retrieve the basic business logics of different verification attribute items based on the coal mine disaster management system, and determine the underlying logic verification focuses of different verification attribute items based on the basic business logics. At the same time, determine the custom verification concerns for different verification attribute items based on the management objectives;

[0112] Determine the verification rules for different verification attribute items based on the data types, and determine the rule contents corresponding to the verification rules based on the underlying logic verification focuses and the custom verification concerns;

[0113] Nest the rule contents with the verification rules to obtain the target verification rules, and obtain the available format requirements for the target verification rules based on the nesting results;

[0114] Perform content writing conversion on the target verification rules based on the available format requirements, obtain the custom rule configuration results based on the content writing conversion results, and perform conversion on the data model based on the custom rule configuration results to obtain the corresponding rule model;

[0115] Based on the management terminal, obtain the pre-application scenarios for the rule model, and extract the scenario limiting factors of the pre-application scenarios;

[0116] Determine the application conditions and requirements for different pre-application scenarios based on the scenario limiting factors, and group-classify the rule models based on the application conditions and requirements to obtain the rule model sets corresponding to each pre-application scenario;

[0117] At the same time, determine the adaptive correction parameters for the rule parameters of each rule model in the corresponding rule model sets based on the application conditions and requirements of different pre-application scenarios, and perform adaptive adjustment on the rule parameters of each rule model based on the adaptive correction parameters to complete the scenario configuration of the rule model.

[0118] In this embodiment, custom rules are configured for the attribute items that need to be verified. For example, by setting basic data values, regular expressions, or custom function rules for the attributes in the model, the data model is converted into a specific rule model. If not set, it means there is no rule;

[0119] For example, setting the regular rule of “^\\d{9}$” for mineCode in the data model means that the data content is required to be 9 characters in length; setting the function rule of “beforeTime(dataTime)” for sensorTime in the data model means that the sensorTime is required to be before the dataTime. The example diagram of custom rule configuration is as Figure 3 shown.

[0120] In this embodiment, the verification target refers to the verification object when verifying various coal mine disaster data and the verification purpose to be achieved during verification.

[0121] In this embodiment, group division refers to the division of multi-dimensional attributes according to the verification target, that is, one verification target can correspond to one dimensional attribute or multiple dimensional attributes.

[0122] In this embodiment, sample representation refers to the specific value and structure of data items of different verification attribute items.

[0123] In this embodiment, the coal mine disaster management system is pre-constructed and used to record the business logic corresponding to different verification attribute items during operation.

[0124] In this embodiment, the focus of underlying logic verification refers to the key points of business logic verification corresponding to different verification attribute items during verification.

[0125] In this embodiment, the management target is known in advance.

[0126] In this embodiment, the custom verification focus refers to the points that need to be additionally verified for different verification attribute items in addition to the focus of underlying logic verification determined according to the basic business logic, and can be added, deleted, and adjusted.

[0127] In this embodiment, the verification rule refers to the specific requirements corresponding to different verification attribute items during verification. For example, it can be to verify the value, etc.

[0128] In this embodiment, the rule content refers to the specific content corresponding to the verification rule. For example, when the verification rule is numerical verification, the rule content is the specific numerical requirements, and when the verification rule is a custom function, the rule content is the specific function expression, etc.

[0129] In this embodiment, the target verification rule refers to the result obtained by binding the determined verification rule and rule content, that is, the rule that can be finally applied.

[0130] In this embodiment, the available format requirement refers to the format that the target verification rule can use during deployment.

[0131] In this embodiment, the rule model refers to the result obtained by processing the data model according to the obtained custom rule configuration result, that is, the result obtained by converting the specific content under the data model through verification rules.

[0132] In this embodiment, the pre-application scenario refers to the specific scenario or business that the rule model can use.

[0133] In this embodiment, the scenario limiting factor refers to the requirements for the rule model during operation in different pre-application scenarios, that is, the characteristics during the operation of different pre-application scenarios.

[0134] In this embodiment, the rule model set refers to all rule models corresponding to different pre-application scenarios.

[0135] In this embodiment, the rule parameter refers to the specific requirements and parameters corresponding to the verification rules included in each rule model.

[0136] The working principle and beneficial effects of the above technical solution are as follows: By determining the verification target for various coal mine disaster data, the verification attribute items are determined according to the verification target, and then the underlying logic verification focus and custom verification focus of different verification attribute items are locked. Secondly, according to the data type, underlying logic verification focus and custom verification focus, the verification rules and rule contents for different verification attribute items are determined, the target verification rules are effectively formulated, and the obtained target verification rules are converted in content writing to effectively obtain the custom rule configuration result. Finally, the data model is converted through the custom rule configuration result to obtain the corresponding rule model, and the rule model is configured for scenarios, ensuring that different scenarios correspond to different rule models, thereby improving the automatic verification efficiency and verification accuracy of coal mine disaster data in different scenarios.

[0137] Embodiment 5:

[0138] Based on Embodiment 1, this embodiment provides a method for automatically verifying various coal mine disaster data. In step 2, the disaster indicators are associated with the custom rule configuration and scenario configuration results to obtain an automatic verification model for coal mine disaster data, including:

[0139] Obtain disaster indicators and receive the scenario association instruction for the disaster indicators submitted by the management user based on the configuration page;

[0140] Determine the association relationship between the disaster indicators and the scenario configuration results based on the scenario association instruction, and generate a drainage reference table for the disaster data based on the association relationship;

[0141] Perform routing adaptation of the data flow interface for the custom rule configuration and scenario configuration results based on the drainage reference table, and obtain an automatic verification model for coal mine disaster data based on the routing adaptation result.

[0142] In this embodiment, the configuration page is an online configuration interface that can submit configuration requirements.

[0143] In this embodiment, the scenario association instruction refers to the scenarios corresponding to different disaster indicators submitted through the configuration page.

[0144] In this embodiment, the drainage reference table is generated based on the association relationship between the disaster indicators and the scenario configuration results, and is used to guide different disaster data to flow into the corresponding rule models.

[0145] The working principle and beneficial effects of the above technical solution are as follows: Obtain the production and economic association instructions of different disaster indicators for users through the configuration page, determine the association relationship between the disaster indicators and the scenario configuration results according to the scenario association instructions, and then generate a drainage reference table for disaster data according to the association relationship. Finally, perform routing adaptation of the data flow interface for the custom rule configuration and scenario configuration results through the drainage reference table, so as to accurately and effectively construct an automatic verification model for coal mine disaster data, providing great convenience and guarantee for automatically verifying various coal mine disaster data.

[0146] Embodiment 6:

[0147] Based on Embodiment 1, this embodiment provides a method for automatically verifying various coal mine disaster data. As Figure 4 shown, in step 3, perform model parsing on the accessed disaster data stream based on the automatic verification model for coal mine disaster data, determine the corresponding verification rules, and perform data verification on the disaster data stream based on the verification rules, including:

[0148] Obtain the disaster data stream, input the disaster data stream into the automatic verification model for coal mine disaster data for model parsing, and obtain the specific verification rules corresponding to the disaster data stream;

[0149] Divide the disaster data stream into data groups to be verified respectively based on the attribute limitation requirements of the specific verification rules. At the same time, extract the verification dimensions of the specific verification rules, and map and match the specific verification rules with the data groups to be verified based on the verification dimensions;

[0150] Based on the mapping and matching results, call the entire verification process corresponding to the specific verification rules to automatically verify the data groups to be verified under the corresponding verification dimensions.

[0151] In this embodiment, the data verification example diagram is as Figure 4 shown.

[0152] In this embodiment, the specific verification rule refers to the data verification rule applicable to the current disaster data stream.

[0153] In this embodiment, the attribute limitation requirement refers to the verification process, conditions, etc. corresponding to the specific verification rule.

[0154] In this embodiment, the verification dimension refers to the aspect where the specific verification rule needs to verify the data, that is, the specific requirements to be verified.

[0155] The working principle and beneficial effects of the above technical solution are as follows: By inputting the disaster data stream into the automatic verification model of coal mine disaster data for model parsing, accurate and effective locking of the specific verification rules corresponding to the disaster data stream is achieved. Secondly, the obtained specific verification rules are parsed to realize the division of the data to be verified into data groups according to the specific verification rules, and then automatic data verification of the data groups to be verified under the corresponding verification dimension is realized according to the verification dimension of the specific verification rule, improving the efficiency and accuracy of data verification.

[0156] Embodiment 7:

[0157] Based on Embodiment 1, this embodiment provides a method for automatically verifying various coal mine disaster data. As Figure 5 shown, in step 4, the data verification results are recorded and analyzed to generate a verification report of the verification results and analysis results, including:

[0158] Obtain the data verification results of the coal mine disaster data and record the data verification results;

[0159] Based on the recorded results, split the data verification results into a set of verified data and a set of unverified data, and trace the source data of the set of unverified data to obtain the corresponding original coal mine disaster data and the reasons for non-verification;

[0160] Configure the original coal mine disaster data and the reasons for non-verification corresponding to the set of unverified data as a drill-down data viewing list;

[0161] At the same time, generate a comparison chart of the set of verified data and the set of unverified data based on the verification time, and associate and bind the drill-down data viewing list with the corresponding set of unverified data in the comparison chart;

[0162] Generate a verification report of the verification results and analysis results based on the association and binding results.

[0163] In this embodiment, the comparison chart of the set of verified data and the set of unverified data is as Figure 5 shown.

[0164] In this embodiment, the verification report includes basic verification information (verification date, verification object, verification scope, verification purpose), verification methods (rule parsing, data type judgment, regular expression judgment, function method judgment), verification results (overall success and failure ratios, detailed results), and improvement suggestions.

[0165] In this embodiment, the source data tracing of the unqualified verification set refers to the search for the original data of the unqualified verification set.

[0166] In this embodiment, the drill-down data view list refers to setting the original coal mine disaster data and the reasons for failed verification as a detailed list, and the corresponding specific information can be viewed by clicking when the user needs to view.

[0167] The working principle and beneficial effects of the above technical solution are as follows: By recording the data verification results of coal mine disaster data and splitting the recorded verification results, the qualified verification set and the unqualified verification set are effectively determined. Secondly, the source data tracing of the unqualified verification set is carried out to determine the original coal mine disaster data and the reasons for failed verification, and a drill-down data view list is generated. Finally, a comparison chart of the qualified verification set and the unqualified verification set is generated, and the drill-down data view list is associated and bound with the corresponding unqualified verification set in the comparison chart, which is convenient for users to comprehensively and effectively view the verification situation of coal mine disaster data.

[0168] Embodiment 8:

[0169] Based on Embodiment 1, this embodiment provides a method for automatically verifying various coal mine disaster data. In step 4, the viewing management of the verification report includes:

[0170] Obtaining the verification report and determining the viewing method of the verification report, where the viewing method includes preview, download, and print;

[0171] Configuring the background management parameters of the verification report based on the viewing method, and opening multi-channel viewing permissions for the verification report based on the background management parameter configuration;

[0172] Effectuating the permissions of the verification report based on the multi-channel viewing permissions to complete the viewing management of the verification report.

[0173] In this embodiment, the multi-channel viewing permission refers to the configuration of the permissions of the verification report, that is, different user identities correspond to different viewing permissions.

[0174] The working principle and beneficial effects of the above technical solution are as follows: By managing the viewing method and configuring the permissions of the verification report, the reliability of the viewing management of the verification report is ensured, and the security and reliability of the data are ensured.

[0175] Example 9:

[0176] This embodiment provides a system for automatically verifying various coal mine disaster data, as Figure 6 shown, including:

[0177] A data model construction module, configured to obtain expected coal mine disaster data to be verified, and determine formatting parameters for the coal mine disaster data based on the multi-dimensional attributes of the expected coal mine disaster data to construct a data model;

[0178] A verification model construction module, configured to perform custom rule configuration and scenario configuration on the data model based on verification attribute items, and associate disaster indicators with the results of the custom rule configuration and scenario configuration to obtain an automatic verification model for coal mine disaster data;

[0179] A data verification module, configured to perform model parsing on the accessed disaster data stream based on the automatic verification model for coal mine disaster data to determine corresponding verification rules, and perform data verification on the disaster data stream based on the verification rules;

[0180] A verification report management module, configured to record and analyze the data verification results, generate a verification report of the verification results and analysis results, and view and manage the verification report.

[0181] The working principle and beneficial effects of the above technical solution are as follows: By determining the multi-dimensional attributes of the expected coal mine disaster data to be verified and determining the formatting parameters for the coal mine disaster data according to the multi-dimensional attributes, an effective construction of the data model is realized. Secondly, custom rule configuration and scenario configuration are performed on the data model according to the verification attribute items, and the disaster indicators are associated with the configuration results, so as to effectively construct an automatic verification model for coal mine disaster data, which provides convenience and guarantee for the automatic verification of coal mine disaster data. Finally, through the parsing and data verification of the accessed disaster data stream by the automatic verification model for coal mine disaster data, and generating corresponding verification reports according to the verification results and viewing and managing the verification reports, the efficiency and accuracy of the automatic verification of coal mine disaster data are ensured. At the same time, the automated processing reduces manual participation, and the custom standardized rules and scenarios can flexibly and efficiently perform verification work on data of different disasters.

[0182] Example 10:

[0183] Based on Example 9, this embodiment provides a system for automatically verifying various coal mine disaster data. The data model construction module includes:

[0184] A data acquisition unit, configured to obtain the system composition of the coal mine and determine the original disaster data generated during the operation of the coal mine based on the system composition;

[0185] An attribute determination unit, configured to:

[0186] Based on the original disaster data, obtain the expected coal mine disaster data to be verified, and extract the data status characterization of the expected coal mine disaster data to be verified;

[0187] Based on the data status characterization, divide the preset coal mine disaster data to be verified into disaster data types, and based on the disaster data type division result, access the coal mine disaster knowledge base to determine the management dimension for each disaster data type;

[0188] Based on the management dimension, obtain the multi-dimensional attributes of the expected coal mine disaster data to be verified under each disaster data type.

[0189] The working principle and beneficial effects of the above technical solution are as follows: By determining the system composition of the coal mine, the original disaster data generated during the operation of the coal mine can be determined through the system composition, and then the expected coal mine disaster data to be verified can be locked. Secondly, the data status characterization of the expected coal mine disaster data to be verified is determined to realize the division of disaster data types and the determination of the management dimension for each disaster data type according to the data status characterization. Finally, the multi-dimensional attributes of the expected coal mine disaster data to be verified under each disaster data type are obtained according to the management dimension, which provides convenience for the automatic verification of coal mine disaster data.

[0190] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention also intends to include these changes and modifications.

Claims

1. A method for automatically verifying data on multiple disasters in coal mines, characterized in that, Including: Step 1: Obtain the expected coal mine disaster data to be verified, and determine the formatting parameters for the coal mine disaster data based on the multi-dimensional attributes of the expected coal mine disaster data to construct a data model. Here, it refers to the result obtained after formatting and defining the coal mine disaster data with multi-dimensional attributes, and is used to represent the specific formatting steps or standards for the coal mine disaster data; Step 2: Based on the verification attribute items, perform custom rule configuration and scenario configuration on the data model, and associate the disaster indicators with the results of the custom rule configuration and scenario configuration to obtain an automatic verification model for coal mine disaster data. Here, the automatic verification model for coal mine disaster data refers to the finally obtained tool capable of verifying coal mine disaster data; Step 3: Based on the automatic verification model for coal mine disaster data, perform model parsing on the accessed disaster data stream, determine the corresponding verification rules, and perform data verification on the disaster data stream based on the verification rules; Step 4: Record and analyze the data verification results, generate a verification report of the verification results and analysis results, and view and manage the verification report; Among them, constructing the data model includes: Obtain the multi-dimensional attributes of the expected coal mine disaster data to be verified, and determine the semantic features of each dimension attribute; At the same time, based on the management terminal, obtain the verification process and verification operations of each dimension attribute in the expected coal mine disaster data of different categories, and determine the differentiated format requirements for each dimension attribute in the expected coal mine disaster data of different categories based on the semantic features, verification process and verification operations; Determine the formatting parameters for the coal mine disaster data based on the differentiated format requirements, and classify and record the formatting parameters of different dimension attributes of different categories of coal mine disaster data to obtain a data model; Among them, obtaining the automatic verification model for coal mine disaster data includes: Obtain the disaster indicators, and receive the scenario association instructions for the disaster indicators submitted by the management user based on the configuration page; Determine the association relationship between the disaster indicators and the scenario configuration results based on the scenario association instructions, and generate a drainage reference table for the disaster data based on the association relationship; Based on the drainage reference table, perform routing adaptation on the data stream interfaces of the custom rule configuration and scenario configuration results, and obtain the automatic verification model for coal mine disaster data based on the routing adaptation results.

2. The method for automatically verifying various disaster data in a coal mine according to claim 1, wherein In Step 1, obtaining the expected coal mine disaster data to be verified includes: Obtain the system composition of the coal mine, and determine the original disaster data generated during the operation of the coal mine based on the system composition; Obtain the expected coal mine disaster data to be verified based on the original disaster data, and extract the data status representation of the expected coal mine disaster data; Based on the data status representation, perform disaster data type classification on the preset coal mine disaster data to be verified, and access the coal mine disaster knowledge base based on the disaster data type classification results to determine the management dimensions for each disaster data type; Obtain the multi-dimensional attributes of the expected coal mine disaster data under each disaster data type based on the management dimensions.

3. The method for automatically verifying various disaster data in a coal mine according to claim 1, characterized in that, In Step 2, performing custom rule configuration and scenario configuration on the data model based on the verification attribute items includes: Based on the management terminal, obtain the verification objectives for various coal mine disaster data, and group-divide the multi-dimensional attributes of the expected verified coal mine disaster data based on the verification objectives to obtain the verification attribute items corresponding to each verification objective; Determine the sample representations of different verification attribute items under each verification objective respectively, and determine the data types of different verification attribute items based on the sample representations; Retrieve the basic business logics of different verification attribute items based on the coal mine disaster management system, and determine the underlying logic verification focuses of different verification attribute items based on the basic business logics. At the same time, determine the custom verification concerns for different verification attribute items based on the management objectives; Determine the verification rules for different verification attribute items based on the data types, and determine the rule content corresponding to the verification rules based on the underlying logic verification focuses and custom verification concerns; Nest the rule content with the verification rules to obtain the target verification rules, and obtain the available format requirements for the target verification rules based on the nesting results; Perform content writing conversion on the target verification rules based on the available format requirements, and obtain the custom rule configuration results based on the content writing conversion results. And perform conversion on the data model based on the custom rule configuration results to obtain the corresponding rule model; Based on the management terminal, obtain the pre-application scenarios for the rule model, and extract the scenario limiting factors of the pre-application scenarios; Determine the application conditions and requirements for different pre-application scenarios based on the scenario limiting factors, and group-classify the rule models based on the application conditions and requirements to obtain the rule model sets corresponding to each pre-application scenario; At the same time, determine the adaptive correction parameters for the rule parameters of each rule model in the corresponding rule model sets based on the application conditions and requirements of different pre-application scenarios, and perform adaptive adjustment on the rule parameters of each rule model based on the adaptive correction parameters to complete the scenario configuration of the rule models.

4. A method for automatically verifying various disaster data in a coal mine according to claim 1, characterized in that, In step 3, based on the coal mine disaster data automatic verification model, perform model parsing on the accessed disaster data stream, determine the corresponding verification rules, and perform data verification on the disaster data stream based on the verification rules, including: Obtain the disaster data stream, and input the disaster data stream into the coal mine disaster data automatic verification model for model parsing to obtain the specific verification rules corresponding to the disaster data stream; Group-divide the data groups to be verified for the disaster data stream respectively based on the attribute limitation requirements of the specific verification rules. At the same time, extract the verification dimensions of the specific verification rules, and map and match the specific verification rules with the data groups to be verified based on the verification dimensions; Based on the mapping and matching results, retrieve the entire verification process corresponding to the specific verification rules to perform automatic data verification on the data groups to be verified under the corresponding verification dimensions.

5. A method for automatically verifying various disaster data in a coal mine according to claim 1, characterized in that, In step 4, record and analyze the data verification results to generate a verification report of the verification results and analysis results, including: Obtain the data verification results for the coal mine disaster data, and record the data verification results; Based on the recorded results, split the data verification results into a set of verified data and a set of unverified data, and trace the source data of the set of unverified data to obtain the corresponding original coal mine disaster data and the reasons for non-verification. Configure the original coal mine disaster data corresponding to the set of failed verifications and the reasons for the failed verifications as the drill-down data viewing list; Meanwhile, generate a comparison chart of the set of passed verifications and the set of failed verifications based on the verification time, and associate and bind the drill-down data viewing list with the corresponding set of failed verifications in the comparison chart; Generate a verification report on the verification results and analysis results based on the associated binding results.

6. The method for automatically verifying various disaster data in a coal mine according to claim 1, characterized in that, In step 4, view and manage the verification report, including: Obtain the obtained verification report and determine the viewing method of the verification report, where the viewing methods include preview download and printing; Configure the background management parameters for the verification report based on the viewing method, and enable multi-channel viewing permissions for the verification report based on the background management parameter configuration; Effect the permissions for the verification report based on the multi-channel viewing permissions to complete the viewing and management of the verification report.

7. A system for automatically verifying various disaster data in coal mines, which is a method for automatically verifying various disaster data in coal mines according to claim 1, characterized in that, Including: A data model construction module for obtaining the expected coal mine disaster data to be verified and determining the formatting parameters for the coal mine disaster data based on the multi-dimensional attributes of the expected coal mine disaster data to construct a data model; A verification model construction module for customizing rule configuration and scenario configuration for the data model based on the verification attribute items, and associating the disaster indicators with the results of the custom rule configuration and scenario configuration to obtain an automatic verification model for coal mine disaster data; A data verification module for parsing the disaster data stream accessed based on the automatic verification model for coal mine disaster data to determine the corresponding verification rules, and performing data verification on the disaster data stream based on the verification rules; A verification report management module for recording and analyzing the data verification results, generating a verification report on the verification results and analysis results, and viewing and managing the verification report.

8. A system for automatically verifying multiple disaster data in coal mines according to claim 7, characterized in that, The data model construction module includes: A data acquisition unit for obtaining the system composition of the coal mine and determining the original disaster data generated during the operation of the coal mine based on the system composition; An attribute determination unit for: Obtaining the expected coal mine disaster data to be verified based on the original disaster data and extracting the data state representation of the expected coal mine disaster data; Dividing the preset coal mine disaster data to be verified into disaster data types based on the data state representation, and accessing the coal mine disaster knowledge base based on the disaster data type division results to determine the management dimensions for each disaster data type; Obtaining the multi-dimensional attributes of the expected coal mine disaster data under each disaster data type based on the management dimensions.

Images